4.8 Article

Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome

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NATURE COMMUNICATIONS
卷 12, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41467-020-20578-2

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资金

  1. National Human Genome Research Institute of the National Institutes of Health [R01MH101814, 5U24HG009446]
  2. Spanish Ministry of Economy, Industry and Competitiveness (MEIC) [BIO201570777-P]
  3. Agencia Estatal de Investigacion/European Regional Development Fund (ERDF) [PGC2018-094017-B-100]
  4. Chan Zuckerberg Initiative [CZF2019-002436]
  5. Common Fund of the Office of the Director of the National Institutes of Health
  6. 'la Caixa'-Severo Ochoa pre-doctoral fellowship [LCF/BQ/SO15/52260001]
  7. Secretaria d'Universitats i Recerca del Departament d'Empresa i Coneixement (Generalitat de Catalunya) [2017FI_B 00722]
  8. European Social Fund (ESF)
  9. Spanish Ministry of Economy, Industry and Competitiveness (MEIC)
  10. Centro de Excelencia Severo Ochoa
  11. CERCA Programme/Generalitat de Catalunya
  12. European Regional Development Fund (ERDF)

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Alternative splicing is a fundamental step in eukaryotic mRNA biogenesis, and the comprehensive catalog of splicing QTLs in the human genome generated through analysis of the GTEx dataset provides insight into splicing regulation mechanisms and disease mechanisms.
Alternative splicing (AS) is a fundamental step in eukaryotic mRNA biogenesis. Here, we develop an efficient and reproducible pipeline for the discovery of genetic variants that affect AS (splicing QTLs, sQTLs). We use it to analyze the GTEx dataset, generating a comprehensive catalog of sQTLs in the human genome. Downstream analysis of this catalog provides insight into the mechanisms underlying splicing regulation. We report that a core set of sQTLs is shared across multiple tissues. sQTLs often target the global splicing pattern of genes, rather than individual splicing events. Many also affect the expression of the same or other genes, uncovering regulatory loci that act through different mechanisms. sQTLs tend to be located in post-transcriptionally spliced introns, which would function as hotspots for splicing regulation. While many variants affect splicing patterns by altering the sequence of splice sites, many more modify the binding sites of RNA-binding proteins. Genetic variants affecting splicing can have a stronger phenotypic impact than those affecting gene expression. The profiling of genetic variants affecting splicing can give insight into disease mechanisms. Here, the authors develop a pipeline for discovery of variants affecting splicing (sQTLs) and with application to the GTEx dataset they generate a catalog of human sQTLs.

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